Telematics furtherance visualization system

ABSTRACT

A method and apparatus for use in a mobile device telemetry system is disclosed. The method and apparatus relate to a telematics furtherance visualization system. The system can sense mobile device remote observation misalignment risk and reconcile mobile device remote observation alignment by communicating a subsequent log of mobile device vector data for rendering a sequence of next positions in the furtherance of a mobile device. The system can also provide an adaptive rendering based upon a phase shift, a log of mobile device vector data, or predictive rendering until receipt of the next subsequent log of mobile device vector data.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.15/682,615, entitled “Telematics Furtherance Visualization System”,filed Aug. 22, 2017, which is a continuation of U.S. application Ser.No. 15/341,842, entitled “Telematics Furtherance Visualization System”,filed Nov. 2, 2016, which is a continuation of U.S. application Ser. No.14/597,667, entitled “Telematics Furtherance Visualization System”,filed Jan. 15, 2015, each of which is herein incorporated by referencein their entirety.

TECHNICAL FIELD OF THE INVENTION

The present invention generally relates to a method and apparatus for atelemetry furtherance visualization system. More specifically, thepresent invention relates to visualizing the advancement of a mobiledevice as a rendered graphical representation on a digital display basedupon a series of historical logs of mobile device vector data.

BACKGROUND OF THE INVENTION

Mobile Telemetry systems with mobile device rendering capabilities areknown in the prior art. Mobile information may be sensed, logged as dataand transmitted for subsequent data processing and rendering on acomputing device. Data transmission and rendering on a digital map maybe based upon different approaches to receiving a log of data. The logof data may be received randomly and unexpected in time, periodic orexpected at a repeating point in time as well as aperiodic irregularpoints in time. The random and aperiodic approaches can result inrendering positional errors on a graphical map of a computing device.

U.S. Pat. No. 6,845,318 issued on Jan. 18, 2005 to Moore et al. al. andrelates to methods, data structures and systems that provide techniquesfor processing track logs. A track log is represented as a number oftrack points. The track points represent geographic positions previouslytravelled. The track log and the track points are overlaid on a map andpresented on a display in communication with a portable navigationdevice. Track points are graphically selected and identified via thedisplay. Any graphically selected track point is also associated with aselectable operation for immediate, automatic and/or subsequentexecution on a portable navigation device.

United States patent application US201/0047244 published on Nov. 29,2001 to Harrison and Morris. This patent application relates to a datamonitoring apparatus including a GPS receiver, a micro controller, anumber of sensors, a number of actuators, memory, a radio transmitterand a data communication antennae. The apparatus accumulates real timedata concerning position and time and other operational parameters of ageographically mobile object such as a vehicle for transmission to amonitoring station. Transmission channel utility may be improved throughtransmission of accumulated historical data to a separate monitoringstation.

United States patent application US2012/0253862 published on Oct. 4,2012 to Davidson. This patent application relates a fleet managementcomputer system configured for providing a fleet management userinterface. According to various embodiments, the fleet managementcomputer system is configured for assessing operational data todetermine a vehicle travel path and one or more operationalcharacteristics indicated by the operational data. In addition,according to various embodiments, the fleet management computer systemis configured for generating a graphical user interface that include anevaluation results display showing the operational characteristics and ageographical map showing the vehicle travel path.

United States patent application US2012/0303266 published on Nov. 29,2012 to Su et. al. and relates to a mobile computing device that candetermine a first waypoint distance that indicates a distance from thedevice's location within which a first waypoint of a route cannot belocated. This distance can be sent to a server as part of a map datarequest. The distance can be based on a device velocity, a requestlatency time, an instruction intake time and an instruction reactiontime. The request latency time represents the delay from sending arequest to receiving route information in response. The instructionintake time represents the time it takes for a user to read or listen toa first waypoint instruction. The instruction reaction time representsthe time it takes a user to react to a first waypoint instruction. Routeinformation contains information identifying a first waypoint that isfurther away from the device position supplied with the request than thefirst waypoint distance.

U.S. Pat. No. 8,706,348 issued on Apr. 22, 2014 to Beams and Cawse. Thispatent relates to a mobile telemetry apparatus, operable to initiate atelemetry processing operation in response to an aperiodic, non-randomtrigger signal cued by a sensed, operationally variable mobilecondition. A trigger unit provides the trigger signal that in turnswitches the telemetry apparatus from a resource-conserving idle stateto a state in which a session initiates, so that operationally salientvariations in information changes in vehicle sensor data may be detectedand processed.

U.S. Pat. No. 8,032,276 issued on Oct. 4, 2011 to Cawse and U.S. Pat.No. 8,670,928 issued on Mar. 11, 2014 to Cawse. These patents relate toan apparatus and method for optimally recording or transmittingpositional data and events of an object. The apparatus includes an inputmeans to continuously provide positional data to a microprocessor and amemory device to store selected positional data. The microprocessor isprogrammed to compare new positional data from the input means topreviously recorded log of positional data and creates a new log if thenew positional data differs from the previously recorded log inaccordance with pre-determined parameters.

The prior art approaches and in particular the approaches to renderingthe position of a mobile device on a graphical display are deficient.The prior art approaches may result in visualization positional errorsor inconsistent erratic rendering of the position of a mobile devicewhen based upon the receipt of a series of historical logs of mobiledevice vector data.

SUMMARY OF THE INVENTION

The present invention relates to aspects in a mobile device telemetrysystem and provides a new furtherance visualization capability forrendering the position of a mobile device on a graphical display of acomputing device based upon a series of historical logs of mobile devicevector data.

The present invention is directed to aspects in a telematics furtherancevisualization system. The system can sense a mobile device and remoteobservation misalignment risk and reconcile the alignment bycommunicating a subsequent log of mobile device vector data forrendering a sequence of next positions in the furtherance of a mobiledevice. The system can also provide an adaptive rendering based upon aphase shift, a log of mobile device vector data, or predictive renderinguntil receipt of the next subsequent log of mobile device vector.

According to a first broad aspect of the invention, there is atelematics furtherance visualization method. The method includes a firstdistributed process for a mobile device and a second distributed processfor a remote device. The first distributed process and the seconddistributed process capable of communicating messages and data. Thefirst distributed process capable to monitor the mobile device to logand communicate mobile device vector data to the remote device. Thefirst distributed process also capable to sense a mobile device remoteobservation misalignment risk and reconcile mobile device remoteobservation alignment. The second distributed process capable toadaptive render a graphical image of the mobile device from the mobiledevice vector data.

According to a second broad aspect of the invention, there is atelematics furtherance visualization apparatus. The apparatus includesat least one mobile device. The mobile device includes a microprocessor,memory and firmware. The microprocessor, memory and firmware capable ofexecuting a first distributed process. The apparatus includes at leastone remote device. The remote device includes a microprocessor memoryand software. The microprocessor, memory and software capable ofexecuting a second distributed process. The at least one mobile deviceand the at least one remote device capable of communication. A firstdistributed process for a mobile device and a second distributed processfor a remote device. The first distributed process and the seconddistributed process capable of communicating messages and data. Thefirst distributed process capable to monitor said mobile device to logand communicate mobile device vector data to the remote device. Thefirst distributed process capable to sense a mobile device remoteobservation misalignment risk and reconcile mobile device remoteobservation alignment. The second distributed process capable toadaptive render a graphical image of the mobile device from the mobiledevice vector data.

The mobile device remote observation misalignment risk may also includemobile device remote observation alignment parameters, the adaptiverender may also include adaptive render parameters and the mobile deviceremote observation alignment parameters and the adaptive renderparameters may also be correlated.

The reconcile mobile device remote observation alignment may alsoinclude communicating a subsequent log of the mobile device vector data.

The mobile device vector data may also include at least one data pointof a position indication, a speed indication or a heading indication ofthe mobile device and at least one time stamp associated with each datapoint.

The mobile device remote observation alignment parameters may also bebased upon at least one of a position limit, a speed limit, a headinglimit or a path segment limit.

The adaptive render parameters may also be based upon at least one of aphase shift, a data render, or a predictive render.

The mobile device remote observation alignment parameters may also bebased upon at lease one of a position limit, a speed limit, a headinglimit or a path segment limit and the adaptive render parameters mayalso be based upon at least one of a phase shift, a data render, or apredictive render.

In an embodiment of the invention, the path segment limit is 100 rawdata points of mobile device vector data and the phase shift is in therange between −4.5 seconds and −13.5 seconds.

In another embodiment of the invention, the path segment limit is 100raw data points of mobile device vector data and the phase shift issubstantially −9 seconds.

The mobile device remote observation alignment parameters may also bebased upon a combination of at least two of a position limit, a speedlimit, a heading limit, or a path segment limit.

The adaptive render parameters may also be based upon a combination ofat least two of a phase shift, a data render, or a predictive render.

The mobile device remote observation alignment parameters and theadaptive render parameters may also be correlated to command apredictive render.

The mobile device remote observation alignment parameters and theadaptive render parameters may also be calibrated to command apredictive render.

The method and apparatus may also be capable to sense a potential mobiledevice remote observation misalignment risk based upon checking themobile device remote observation alignment parameters.

The method apparatus may also include checking the mobile device remoteobservation alignment parameters to enable the reconcile mobile deviceremote observation.

The method and apparatus wherein the capable to adaptive render is basedupon the adaptive render parameters.

The method and apparatus wherein the checking the mobile device remoteobservation alignment parameters determines a mobile device remoteobservation misalignment risk based upon a position varying beyond alimit.

The method and apparatus wherein the checking the mobile device remoteobservation alignment parameters determines a mobile device remoteobservation misalignment risk based upon a speed limit.

The method and apparatus wherein the checking the mobile device remoteobservation alignment parameters determines a mobile device remoteobservation misalignment risk based upon a heading limit.

The method and apparatus wherein the checking the mobile device remoteobservation alignment parameters determines a mobile device remoteobservation misalignment risk based upon a path segment represented by anumber of raw data points.

The mobile device remote observation alignment parameters and theadaptive render parameters may be recalibrated.

Recalibrated may also be at least one of the mobile device remoteobservation alignment parameters or the adaptive render parameters.

The method and apparatus may also include a heartbeat to further commanda predictive render.

These and other aspects and features of non-limiting embodiments areapparent to those skilled in the art upon review of the followingdetailed description of the non-limiting embodiments and theaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

Exemplary non-limiting embodiments of the present invention aredescribed with reference to the accompanying drawings in which:

FIG. 1 is a high level diagrammatic view of a mobile device telematicscommunication system;

FIG. 2 is diagrammatic view of an mobile telemetry hardware systemincluding an on-board portion and a resident mobile portion;

FIG. 3 is an example illustration of observer time based rendering of amobile device graphical image on a graphical display of a remote device;

FIG. 4 is an example illustration of observer time based rendering amobile device on a graphical image on a graphical display of a remotedevice with potential rendering errors;

FIG. 5 is an example illustration of mobile device actual positions andfurtherance visualization render positions for a relatively constantvelocity and constant speed of the mobile device;

FIG. 6a is an example illustration of mobile device actual positions andfurtherance visualization render positions with potential renderingerrors as a consequence of a mobile device decreasing speed;

FIG. 6b is an example illustration of mobile device actual positions andfurtherance visualization render positions with potential renderingerrors as a consequence of a mobile device increasing speed;

FIG. 7a is an example illustration of mobile device actual positions andfurtherance visualization render positions with potential renderingerrors as a consequence of a left or decreasing heading change;

FIG. 7b is an example illustration of mobile device real positions andfurtherance visualization render positions with potential renderingerrors as a consequence of a right or increasing heading change;

FIG. 8a is an example illustration of first scenario of a mobile devicetravelling along a path segment with real positions and a category ofpotential rendering error arising from decreasing heading changes;

FIG. 8b is an example illustration of a second scenario of a mobiledevice travelling along a path segment with real positions and twocombined categories of potential rendering errors from increasing anddecreasing heading changes;

FIG. 8c is an example illustration of a third scenario of a mobiledevice travelling along a path segment with real positions and twocombined categories of potential rendering errors from decreasing andincreasing heading changes;

FIG. 8d is an example illustration of a fourth scenario of a mobiledevice travelling along a path segment with real positions and acategory of potential rendering error from increasing heading changes;

FIG. 8e is an example illustration of a fifth scenario of a mobiledevice travelling along a path segment with real positions and twocombined categories of potential rendering errors with increasing anddecreasing speed changes;

FIG. 9a is a state machine diagram of the furtherance visualizationstates and transition conditions;

FIG. 9b is an example illustration of an initial log and subsequent logsof mobile device vector data over time with mobile device-remoteobservation alignment, mobile device-remote observation misalignmentrisk, reconciled alignment and adaptive rendering based upon past knownpositions provided by mobile device vector data;

FIG. 10 is an example illustration of four different furtherancevisualization renderings of a mobile device on a graphical image for afirst path segment from point A to point B, a second path segment frompoint C to point D, a third path segment from point E to point F and afourth path segment from point G to point H without rendering positionalerrors;

FIG. 11a is an example illustration of furtherance visualization for afirst path segment from point A to point B, including multiple logs ofmobile device vector data based upon mobile device-remote observationalignment and potential mobile device-remote observation misalignmentrisk;

FIG. 11b is an example illustration of furtherance visualizationrendering a mobile device on a second path segment from point C to pointD, including multiple logs of mobile device vector data based uponmobile device-remote observation alignment and potential mobiledevice-remote observation misalignment risk;

FIG. 11c is an example illustration of furtherance visualizationrendering a mobile device on a third path segment from point E to pointF, including multiple logs of mobile device vector data based uponmobile device-remote observation alignment and potential mobiledevice-remote observation misalignment risk;

FIG. 11d is an example illustration of furtherance visualizationrendering a mobile device on a fourth path segment from point G to pointH, including multiple logs of mobile device vector data based uponmobile device-remote observation alignment and potential mobiledevice-remote observation misalignment risk;

FIG. 12a is a flow chart illustrating the logic of a telematicsfurtherance visualization system process for calibration between themobile device and the remote device;

FIG. 12b is a flow chart illustrating the logic of a telematicsfurtherance visualization system process for recalibration between themobile device and the remote device;

FIG. 13a is a flow chart illustrating the logic of a telematicsfurtherance visualization system mobile device distributed process;

FIG. 13b is a flow chart of the check reconcile mobile device-remoteobservation alignment parameters sub process; and

FIG. 14 is a flow chart illustrating the logic of a telematicsfurtherance visualization system remote device distributed process.

The drawings are not necessarily to scale and may be diagrammaticrepresentations of the exemplary non-limiting embodiments of the presentinvention.

DETAILED DESCRIPTION Telematics Communication System

Referring to FIG. 1 of the drawings, there is illustrated a high leveloverview of a telematics communication system. There is at least onemobile device, for example, a vehicle generally indicated at 11. Personsskilled in the art will appreciate other types of mobile devices arewithin the scope of the invention. The mobile device 11 includes atelemetry hardware system 30 and optionally a resident portion 42.

The telematics communication system provides communication and exchangeof data, mobile device vector data, information, commands, and messagesbetween components in the system such as at least one server 19, atleast one computing device 20 and at least one mobile device 11. Thecomputing device 20 may be a desktop device or further include otherhand held devices or wearable devices.

In one example, the communication 12 is to/from a satellite 13. Themobile device 11 communicates with the satellite 13 that communicateswith a ground-based station 15 that communicates with a computer network18. In an embodiment of the invention, the mobile telemetry hardwaresystem 30 and the remote site 44 (FIG. 1 and FIG. 2) facilitatescommunication 12 to/from the satellite 13. An example mobile telemetryhardware system 03 is the GEOTAB™ vehicle-tracking device (GO™).

In another example, the communication 16 is to/from a cellular network17. The mobile device 11, and server 19 or computing device 20 connectedto a network 18 communicates over the cellular network 17. In anembodiment of the invention, communication 16 to/from the cellularnetwork 17 is facilitated by the mobile telemetry hardware system 30 andthe remote site 44 components.

Computing device 20 and server 19 communicate over the computer network18. The server 19 may include a database and fleet management software10 that runs on a server 19. Clients operating a computing device 20communicate with the application fleet management software 10 running onthe server 19 or computing device 20. Alternative, access to the fleetmanagement software 10 may be provided through cloud computing. Anexample fleet management software 10 system is the myGEOTAB™ product.

In an embodiment of the invention, data, mobile device vector data,information, commands, and messages may be sent from the mobiletelemetry hardware system 30 to the cellular network 17, to the network18, and to the server 19. Computing devices 20 may access the data,mobile device vector data and information on the server 19.Alternatively, data, information, commands, and messages may be sentfrom the computing device 20 or the server 19, to the network 18, to thecellular network 17, and to the mobile telemetry hardware system 30.

In another embodiment of the invention, data, mobile device vector data,information, commands, and messages may be sent from mobile telemetryhardware system to the satellite 13, the ground based station 15, thenetwork 18, and to the server 19. Computing devices 20 may access data,mobile device vector data and information on the server 19. In anotherembodiment of the invention, data, information, commands, and messagesmay be sent from the server 19, to the network 18, the ground basedstation 15, the satellite 13, and to a mobile telemetry hardware system.

In another embodiment of the invention, data, mobile device vector data,information, commands, and messages may be exchanged between the mobiletelemetry hardware system 30 and the computing device 20 over asatellite 13 based network or a cellular network 17. Alternatively, thedata, mobile device vector data, information, commands, and messages maybe exchanged between the mobile telemetry hardware system 30 and theserver 19 over a satellite 13 based network or a cellular network 17.

Mobile Telemetry Hardware System

Referring now to FIG. 2 of the drawings, there is illustrated a mobiletelemetry hardware system generally indicated at 30 and a remote sitegenerally indicated at 44. An on-board portion generally includes: a DTE(data terminal equipment) telemetry microprocessor 31; a DCE (datacommunications equipment) wireless telemetry communicationsmicroprocessor 32; a GPS (global positioning system) module 33; anaccelerometer 34; a non-volatile flash memory 35; and provision for anOBD (on board diagnostics) interface 36 for connection 43 andcommunication with a vehicle network communications bus 37.

The resident mobile portion 42 generally includes: the vehicle networkcommunications bus 37; the ECM (electronic control module) 38; the PCM(power train control module) 40; the ECUs (electronic control units) 41;and other engine control/monitor computers and microcontrollers 39.

While the system is described as having an on-board portion 30 and aresident mobile portion 42, it is also understood that the presentinvention could be a complete resident mobile system or a completeon-board system. In addition, in an embodiment of the invention, amobile telemetry system includes a mobile system and a remote system 44.The mobile system is the mobile telemetry hardware system 30. The mobiletelemetry hardware system 30 is the on-board portion and may include theresident mobile portion 42. In further embodiments of the invention theremote system 44 may be one or all of the server 19, computing device20, and fleet management software 10.

In an embodiment of the invention, the DTE telemetry microprocessor 31includes an amount of internal flash memory for storing firmware tooperate and control the overall system 30. In addition, themicroprocessor 31 and firmware log data, log mobile device vector data,format messages, receive messages, and convert or reformat messages. Inan embodiment of the invention, an example of a DTE telemetrymicroprocessor 31 is a PIC24H microcontroller commercially availablefrom Microchip Corporation.

The DTE telemetry microprocessor 31 interconnects with an externalnon-volatile flash memory 35. In an embodiment of the invention, anexample of the flash memory 35 is a 32 MB non-volatile flash memorystore commercially available from Atmel Corporation. The flash memory 35of the present invention is used for data logging.

The DTE telemetry microprocessor 31 interconnects for communication tothe GPS module 33. In an embodiment of the invention, an example of theGPS module 33 is a Neo-5 commercially available from u-blox Corporation.The Neo-5 provides GPS receiver capability and functionality to themobile telemetry hardware system 30. Alternatively, the DTE telemetrymicroprocessor 31 may interconnect for communication with an externalGPS module through an interface (not shown). The GPS module providesposition data and speed data to the DTE telemetry microprocessor 31 andnon-volatile flash memory 35.

The DTE telemetry microprocessor is further interconnected with the OBDinterface 36 for communication with the vehicle network communicationsbus 37. The vehicle network communications bus 37 in turn connects forcommunication with the ECM 38, the engine control/monitor computers andmicrocontrollers 39, the PCM 40, and the ECU 41.

The DTE telemetry microprocessor has the ability through the OBDinterface 36 when connected to the vehicle network communications bus 37to monitor and receive vehicle data and information from the residentmobile system components for further processing.

As a brief non-limiting example of vehicle data and information, thelist may include: vehicle identification number (VIN), current odometerreading, current speed, engine RPM, battery voltage, engine coolanttemperature, engine coolant level, accelerator peddle position, brakepeddle position, various manufacturer specific vehicle DTCs (diagnostictrouble codes), tire pressure, oil level, airbag status, seatbeltindication, emission control data, engine temperature, intake manifoldpressure, transmission data, braking information, and fuel level. It isfurther understood that the amount and type of vehicle data andinformation will change from manufacturer to manufacturer and evolvewith the introduction of additional mobile technology.

The DTE telemetry microprocessor 31 interconnects for communication withthe DCE wireless telemetry communications microprocessor 32. In anembodiment of the invention, an example of the DCE wireless telemetrycommunications microprocessor 32 is a Leon 100 commercially availablefrom u-blox Corporation. The Leon 100 provides mobile communicationscapability and functionality to the mobile telemetry hardware system 30for sending and receiving data to/from a remote site 44. Alternatively,the communication device could be a satellite communication device suchas an Iridium™ device interconnected for communication with the DTEtelemetry microprocessor 31. Alternatively, there could be a DCEwireless telemetry communications microprocessor 32 and an Iridium™device for satellite communication. This provides the mobile telemetryhardware system 30 with the capability to communicate with at least oneremote site 44.

In embodiments of the invention, a remote system 44 could be anothervehicle 11 or a base station or other computing device (not shown). Thebase station may include one or more servers 19 and one or morecomputers 20 connected through a computer network 18 (see FIG. 1). Inaddition, the base station may include fleet management applicationsoftware 10 for data acquisition, analysis, and sending/receivingcommands or messages to/from the mobile telemetry hardware system 30.

The DTE telemetry microprocessor 31 interconnects for communication withan accelerometer (34). An accelerometer (34) is a device that measuresthe physical acceleration experienced by an object. Single andmulti-axis models of accelerometers are available to detect themagnitude and direction of the acceleration, or g-force, and the devicemay also be used to sense orientation, coordinate acceleration,vibration, shock, and falling.

In an embodiment of the invention, an example of a multi-axisaccelerometer (34) is the LIS302DL MEMS Motion Sensor commerciallyavailable from STMicroelectronics. The LIS302DL integrated circuit is anultra compact low-power three axes linear accelerometer that includes asensing element and an IC interface able to take the information fromthe sensing element and to provide the measured acceleration data toother devices, such as a DTE Telemetry Microprocessor (31), through anI2C/SPI (Inter-Integrated Circuit) (Serial Peripheral Interface) serialinterface. The LIS302DL integrated circuit has a user-selectablefull-scale range of +−2 g and +−8 g, programmable thresholds, and iscapable of measuring accelerations with an output data rate of 100 Hz or400 Hz.

Alternatively, the mobile device 30 may not include an integral GPSmodule 33 or may not include a DCE wireless telemetry communicationsprocessor 32. With this alternative embodiment of the mobile device 30,an I/O expander (not shown) provides an interface between the DTEtelemetry microprocessor 31 and an external GPS module 33 or a DCEwireless telemetry communications processor 32.

The mobile telemetry hardware system 30 receives data and informationfrom the resident mobile portion 42, the GPS module 33, and theaccelerometer 43. The data and information is stored in non-volatileflash memory 35 as a data log. The data log (including mobile devicevector data) may be transmitted by the mobile telemetry hardware system30 over the mobile telemetry communication system to the server 19 orcomputing device 20 (see FIG. 1). The transmission may be controlled andset by the mobile telemetry hardware system 30 at pre-defined intervalsor aperiodic intervals. The transmission may also be triggered becauseof an event such as a harsh event or an accident. The transmission mayfurther be requested by a command sent from the application softwarerunning on the server 19.

The DTE telemetry microprocessor 31 and non-volatile flash memory 35cooperate to store and execute the firmware, logic, associated data andmobile device vector data for the telematics furtherance visualizationsystem process (Mobile Device) 280, 290 (see FIG. 13a and FIG. 13b ).The GPS module 33 provides mobile device position data and optionallyspeed data to the DTE telemetry microprocessor 31 and non-volatile flashmemory 35 for use with the telematics mobile device furtherancevisualization system process 280. Heading data may also be determinedand logged. The DCE wireless telemetry communications microprocessor 32provides the communication capability to send initial mobile devicevector data to a remote device and subsequent mobile device vector datato a remote system 44.

The remote system 44 components (server 19, computing device 20)cooperate to access the fleet management software 10. The fleetmanagement software 10 cooperates to execute the logic and associateddata and mobile device vector data for the telematics furtherancevisualization system process (Remote Device) 300 (see FIG. 14).

Time Based Mobile Device Positions and Potential Rendering Errors

Time based positions of a mobile device and potential rendering errorsof a graphical image 54 of a mobile device travelling along a pathsegment 56 from point A to point B is next described with reference toFIGS. 3 and 4.

Monitoring a mobile device 11 occurs by the telemetry hardware system 30and associated firmware creating a log of mobile device vector data. Alog of mobile device vector data includes at least one data point andmobile device vector data includes at least one of a position (latitudeand longitude), speed or heading. Each data point is further associatedwith a corresponding time stamp. Sequential logs of mobile device vectordata are communicated over time to a remote system 44. Upon receipt ofthe mobile device vector data, the remote system 44 renders a movinggraphical image 54 upon a map 50 of a digital display of a computingdevice 20.

In this first example (FIG. 3), the mobile device starts at point A andtravels along a desired curvilinear path segment 56 to the destinationpoint B. For this example, both memory to store data and communicationbandwidth are unrestricted and there is a relatively small amount ofdelay between logging the mobile device vector data and subsequentcommunication of the log of mobile device vector data to the remotesystem 44. The time between receipts of sequential logs of mobile devicevector data by the remote device 44 is minimal such that a subsequentlog is received before rendering the current log is completed. Thispermits a contiguous rendering based upon the sequential logs of mobiledevice vector data without the need for adaptive rendering of thegraphical image 54 on a map 50. As the mobile device 11 travels alongthe desired curvilinear path segment 56, the graphical image 54 of themobile device 11 is rendered and updated to reveal the path travelled 52by the mobile device 11 without any associated potential renderingerrors for the rendered path travelled 52.

However, memory to store data and communication bandwidth tend to berestricted or limited in telemetry systems due to capacity and expense.As a result, communication of sequential logs of mobile device vectordata to the remote system 44 can be delayed or aperiodic depending uponthe techniques to communicate the logs and minimize the timing andamount of communication to reduce cellular or satellite expense. Inaddition, techniques to compress the mobile device vector data, optimizethe mobile device vector data or minimize the data may also render theamount of data points in each log of mobile device vector data differentand may introduce aperiodic dependencies.

In a second example (FIG. 4), communication of subsequent logs of mobiledevice vector data may be delayed or aperiodic or contain differentamounts of data points in each subsequent log of mobile device vectordata. This may introduce a risk for potential rendering errors. A delayin receipt of a subsequent log may cause a misalignment between themobile device 11 and the remote system 44 that renders the image 54 on agraphical display of the remote device 44. This further requires theremote device 44 to continue rendering positions of the mobile device 11based upon predicting the furtherance or advancement (future or nextpositions) of a mobile device 11 from the current log of mobile devicevector data. If the remote device 44 completes rending of the mobiledevice 11 based upon the current log and before receipt of the nextsubsequent log in the sequence, the remote device 44 must renderpredicted positions of the mobile device based upon the current log ofmobile device vector data or pause rendering the graphical image 54.

The mobile device begins at point A and travels the desired curvilinearpath segment 56 to the destination point B. The graphical image 54 isrendered upon the map 50. Rendering begins along the first path portion62 and due to the communication delay or irregular timing of thecommunication of a subsequent log of mobile device vector data, a firstrendering positional error 64 occurs. Upon receipt of a subsequent logof mobile device vector data, the remote device 44 corrects the firstrendering positional error 64 and renders the mobile device along thesecond path portion 66. Then, a second rendering positional error 68occurs due to another communication delay or irregular timing of thecommunication of a subsequent log of mobile device vector data. Uponreceipt of the next log of mobile device vector data in the sequence,the remote device 44 corrects the second rendering positional error 68and renders the mobile device along the third path portion 70 until thenext rendering positional error 72 occurs and subsequent correctionalong the next path portion 74. As illustrated in FIG. 4, the frequencyand extent of the risk and associated rending errors is unpredictableand irregular resulting in a deficient representation of the pathtravelled by mobile device 11 on the map 50.

Potential Rendering Errors and Categories of Mobile Device-RemoteObservation Alignment and Misalignment Risks

The different categories, combinations of potential rendering errors andmobile device-remote observation alignment and misalignment risk arenext described with reference to FIGS. 5, 6 a, 6 b, 7 a, 7 b, 8 a, 8 b,8 c, 8 d and 8 e.

The mobile device furtherance rendered positions 86 may be accuratelypredicted and rendered between receipt of subsequent logs of mobiledevice vector data 82 when the change in position of the mobile device11 occurs with a relatively constant speed and relatively constantheading on a relatively linear path segment. This is generally indicatedat 80 in FIG. 5. In this situation, the actual mobile device positions84 are in mobile device-remote observation alignment with thefurtherance rendered positions 86 and the data points in the log ofmobile device vector data 82 reflect the relatively constant speed andrelatively constant heading. Alternatively, the speed and heading may bederived from the data points of positional data to reveal the speed andheading information.

A first type of potential rending error (FIG. 6a ) can occur when themobile device 11 decreases speed on a relatively constant heading orrelatively linear path segment. This causes a decreasing speed mobiledevice-remote observation misalignment 90 over time between the actualmobile device positions 92 and the mobile device furtherance renderedpositions 86. The potential error (e1, e2) increases between data pointsin subsequent logs of mobile device vector data 82.

A second type of potential rendering error (FIG. 6b ) can occur when themobile device 11 increases speed on a relatively constant heading orstraight path segment. This causes an increasing speed mobiledevice-remote observation misalignment 100 over time between the actualmobile device positions 102 and the mobile device furtherance renderedpositions 86. The potential error (e1, e2) increases between data pointsin subsequent logs of mobile device vector data 82.

A third type of potential rendering error (FIG. 7a ) can occur when themobile device 11 decreases (left or counterclockwise turn) a headingwith a relatively constant speed. This causes a decreasing headingmobile device-remote observation misalignment 110 over time betweenactual mobile device positions 112 and the mobile device furtherancerendered positions 86. The potential error (e1, e2) increases betweendata points in subsequent logs of mobile device vector data 82.

A forth type of potential rendering error (FIG. 7b ) can occur when themobile device 11 increases (right or clockwise turn) a heading with arelatively constant speed. This causes an increasing heading mobiledevice-remote observation misalignment 120 over time between the actualmobile device positions 122 and the mobile device furtherance renderedpositions 86. The potential error (e1, e2) increases between data pointsin subsequent logs of mobile device vector data.

In summary, there are four distinct types of potential rendering errorsthat may occur alone or in combinations of speed and heading changes.These potential rendering errors also relate to a transition from arelatively linear path segment to a relatively curved path segment. Whenthe mobile device-remote observation misalignment and potentialrendering errors occur in a combination, the error increases faster overtime.

The four distinct types of potential rendering errors along a portion ofa path segment can be additionally grouped into categories and combinedin different sequences to represent many different path segments asillustrated by the five example scenarios illustrated in FIGS. 8a, 8b,8c, 8d and 8 e.

The path segment for example scenario one is generally indicated at 130in FIG. 8a . This path segment example begins with Case B, an area ofmobile device-remote observation misalignment risk. This is followed bya transition to a segment of mobile device-remote observation alignment,Case A. Then the path segment concludes with a second occurrence of CaseB. Case A occurs for a relatively linear path segment where the speedand heading of the mobile device 11 are relatively constant. Case Boccurs primarily due to a decreasing heading of the mobile device 11.

The path segment for example scenario two is generally indicated at 140in FIG. 8b . This example path segment begins with Case C, an area ofmobile device-remote observation misalignment risk followed by atransition to Case A and a final transition to Case B. Case C occursprimarily due to a increasing heading of the mobile device 11.

The path segment for example scenario four is generally indicated at 160in FIG. 8d . This example path segment begins with Case C followed by atransition to Case A and a final transition to Case C.

The path segment for example scenario five is generally indicated at 170in FIG. 8C. This example path segment begins with Case D followed by atransition to Case A and a final transition to Case E. Case D is asituation of mobile device-remote observation misalignment risk andoccurs primarily due to an increasing speed of the mobile device 11.Case E is also a situation of mobile device-remote observationmisalignment risk primarily due to the decreasing speed of the mobiledevice.

In summary, a path segment for a mobile device 11 may be represented bya combination of one or more of the categories (Case A for mobiledevice-remote observation alignment, and Case B, C, D, and E for mobiledevice-remote observation misalignment risk and the associatedtransitions between the categories.

Furtherance Visualization States and Mobile Device-Remote ObservationAlignment and Misalignment Transitions

The category for mobile device-remote observation alignment (Case A),relatively linear path segments, the four categories for misalignment(Case B, C, D, and E) and relatively non-linear path segments may befurther associated as transitions between two furtherance visualizationstates. This is generally illustrated at 180 in FIG. 9 a.

The two furtherance visualization states include a mobile device-remoteobservation alignment state and a mobile device-remote observationmisalignment risk state. The initial state is the mobile device-remoteobservation alignment state. The initial state occurs for example when amobile device 11 is stationary.

A state change may occur from mobile device-remote observation alignmentto mobile device-remote observation misalignment based upon theoperation of the mobile device 11 over time and upon the path segment.Cases B, C, D, and E over time cause a transition from the mobiledevice-remote observation alignment state to the mobile device-remoteobservation misalignment state. This can occur when a position isvarying beyond limits, or the speed is increasing or decreasing beyondlimits, or the heading is increasing or decreasing beyond limits. Thismay also occur with combinations of speed and heading changes. Arelatively straight path segment and delay in a subsequent log of dataover time can also cause a transition to the mobile device-remoteobservation misalignment state.

The state can also change from mobile device-remote observationmisalignment back to mobile device-remote observation alignment basedupon the operation of the mobile device 11 and upon the path segment.Case A or a relatively curved path segment and subsequent log of datacan cause over time a transition from the mobile device-remoteobservation misalignment state to the mobile device-remote observationalignment state. This situation can also occur when a position, speedand heading become relatively constant or varying within limits.

Logging and Transmission of Mobile Device Vector Data

Logging and transmission of mobile device vector data is based upon thefurtherance visualization states of mobile device-remote observationalignment and mobile device-remote observation misalignment risk and thetransition conditions. Logging and transmission is next described withrespect to an initial log, subsequent logs, a potential for a mobiledevice-remote observation misalignment risk, a reconcile for mobiledevice-remote observation alignment and an adaptive rendering. This isgenerally indicated at 190 in FIG. 9b . In addition, four illustrativefurtherance rendering examples are described and illustrated in FIGS.10, 11 a, 11 b, 11 c and 11 d.

The mobile telemetry hardware system 30 creates multiple sequential logsof mobile device vector data. These sequential logs are communicatedover time to a remote device 44 (see FIG. 9b ) as generally indicated at190. Furtherance visualization and rendering of a graphical image 54 ona map 50 of a remote device 44 is in mobile device-remote observationalignment with the receipt of the initial log of mobile device vectordata. The remote device 44 performs a data render of the graphical image54 based upon the data points and associated time stamps found in theinitial log of mobile device vector data. Rending each data pointprovides furtherance of the graphical image 54 on the map 50.

The log of mobile device vector data may be based upon differentoptimization processes. An optimization process can reduce the number ofmobile device vector data points in the log. An optimization process canfurther limit the amount of data communication resulting in aperiodicdelays in time concerning transmission and receipt of subsequent logs ofmobile device vector data by the remote device 44. The optimizationprocess can also provide a variable or different amount of data pointsand associated time stamps per log with relatively regular communicationof the logs. The optimization process therefore creates the potentialfor a mobile device-remote observation misalignment risk.

Adaptive rendering provides an interconnection and transition betweenthe initial log and subsequent logs of mobile device vector data. In anembodiment of the invention, adaptive rendering includes a phase shiftbetween the mobile device time represented by the log of mobile devicevector data and remote observation time represented by rendering thegraphical image 54. Mobile device time is based upon GPS time related tothe mobile device position in a time zone. Remote observation time isbased upon any global time zone related to the remote system andobserver. In another embodiment of the invention, adaptive renderinguses the data points from a log when the data is available as a datarender. The amount of data points in each log may be different quantitycausing a variable data render for each log. During periods of mobiledevice-remote observation misalignment risk and when the last data pointin a log is reached before receipt of the next log of mobile devicevector data, in another embodiment of the invention the adaptiverendering can switch to predictive rendering. In an embodiment of theinvention, predictive rendering is based upon an extrapolation of thepositions, heading and speed associated with the current log of mobiledevice vector data. A phase shift controls the amount of predictiverender required before receipt of subsequent logs of mobile devicevector data. Adaptive rendering continues with a data render uponreceipt of the next subsequent log of mobile device vector data.

The mobile telemetry hardware system 30 can sense the risk of a mobiledevice-remote observation misalignment and send a subsequent log ofmobile device vector data to reconcile the mobile device-remoteobservation misalignment with the remote device 44. The remote device 44receives a subsequent log of mobile device vector data and continues theadaptive rendering based upon the subsequent log of mobile device vectordata. This process continues through each subsequent receipt a log ofmobile device vector data. Adaptive rendering and the reconcile andcalibration of mobile device-remote observation alignment is achieved bya coupling of two distributed processes, one located with the mobiletelemetry hardware system 30 and the other located with the remotedevice 44. The coupling links the logic to sense a misalignment risk andreconcile of the mobile device-remote observation misalignment with thelogic to provide a phase shift for the adaptive render.

The first example relates to a journey event 200 with a mobile devicetravelling a segment of a path 184 from a starting point A to adestination point B with a mix of linear path segments and curvilinearpath segments as illustrated on the map 50 in FIGS. 10 and 11 a. In anembodiment of the invention, a journey event 200 is a predeterminedportion or segment of a longer or complete journey travelled by themobile device 11. In an alternative embodiment of the invention for ashort journey, a journey event 200 is the complete journey travelled bythe mobile device 11.

The mobile device 11 begins a journey event at point A on the path 184.An initial log of mobile device vector data 82 is transmitted from themobile telemetry hardware system 30 to a remote system 44. The log mayinclude one or more data points of mobile device vector data 82. Themobile device 11 then enters into a first segment of mobiledevice-remote observation misalignment risk 202. The mobile telemetryhardware system 30 can sense and determine a mobile device-remoteobservation misalignment risk. A series of mobile device vector data(204, 206) are logged and transmitted from the mobile device telemetryhardware system 30 to a remote system 44 to reconcile the mobiledevice-remote observation misalignment risk. In an embodiment of theinvention, the series of mobile device vector data (204, 206) may betransmitted relatively more frequently in time when in the first segmentof mobile device-remote observation misalignment risk 202 as compared toa segment of mobile device-remote observation alignment. In anotherembodiment of the invention, the log may contain a larger sample (higheramount) of mobile device vector data points.

Next, the mobile device 11 enters into a segment of mobile device-remoteobservation alignment 208 where the mobile telemetry hardware system 30senses mobile device-remote observation alignment. Another log of mobiledevice vector data 85 is created and transmitted from the mobiletelemetry hardware system 30 to a remote system 44. In an embodiment ofthe invention, the transmission may be relatively less frequent in timewhen compared to the segment of mobile device-remote observationmisalignment risk (202, 214). In another embodiment of the invention,the log may contain a smaller sample of mobile device vector datapoints.

Next, the mobile device 11 enters into another segment of mobiledevice-remote observation misalignment risk 214. The mobile telemetryhardware system 30 again senses and determines a mobile device-remoteobservation misalignment risk and another series of mobile device vectordata (210, 212) are logged and transmitted from the mobile devicetelemetry hardware system 30 to a remote system 44 relatively morefrequently in time or with relatively more data points in the log. In anembodiment of the invention, the log may contain a larger sample ofmobile device vector data points and associated time stamps.

Then the mobile device 11 enters into another segment of mobiledevice-remote observation alignment and completes the journey at pointB. Another log of mobile device vector data 83 is created andtransmitted from the mobile telemetry hardware system 30 to a remotesystem 44.

The second example relates to an exit event 230 where the mobile device11 is travelling a path 186 from point C to point D. The exit event 230is a sub-event of a journey event. The exit event occurs where themobile device 11 exits a highway and makes a heading change onto anotherpath segment. The mobile telemetry hardware system 30 senses the exitevent 230 in contrast to a lane change at point C. The path segmentincludes a mix of linear and curvilinear segments as illustrated in FIG.11b until the exit event 230 completes at point D.

During the exit event 230, the mobile telemetry hardware system 30senses a segment of mobile device-remote observation misalignment risk222. In an embodiment of the invention, a series of mobile device vectordata (224,226) are logged and may be transmitted from the mobile devicetelemetry hardware system 30 to a remote device 44 more frequently intime to reconcile the mobile device-remote observation misalignment. Inanother embodiment of the invention, the log contains a larger sample ofmobile device vector data points communicated less frequently in time.Again, upon receipt of the log of mobile device vector data, the remotedevice 44 renders the data adaptively to provide a graphical image 54 ona map 50 of the remote device 44.

The third example relates to an intersection event 240 as illustrated bya mobile device travelling a path 188 from point E to point F. Theintersection event is also a sub-event of a journey event 200. Theintersection event example occurs when the mobile device arrives at anintersection and makes a heading change at the intersection. The pathincludes a mix of linear and curvilinear segments as illustrated in FIG.11 c.

Before entering the intersection event 240, the mobile device 11 is in asegment of mobile device-remote observation alignment at point E with acorresponding log of mobile device vector data 82 and transmission to aremote system 44.

During the intersection event 240, the mobile telemetry hardware system30 can sense a segment of mobile device-remote observation misalignmentrisk 232. A series of mobile device vector data (234, 236, 238, 242) arelogged and may be transmitted from the mobile device telemetry hardwaresystem 30 to a remote system 44 relatively more frequently in time. Inanother embodiment of the invention, the log contains a larger sample ofmobile device vector data points communicated less frequently in time.Then, the mobile device 11 enters into a segment of mobile device-remoteobservation alignment at point F. Another log of mobile device vectordata 83 is created and transmitted from the mobile telemetry hardwaresystem 30 to a remote system 44. Again, upon receipt of the log ofmobile device vector data, the remote device 44 renders the dataadaptively to provide a graphical image 54 on a map 50 of the remotedevice 44.

The fourth example relates to a mobile device travelling a path 182 frompoint G to point H where a speed event 250 occurs. The speed event 250may be a sub event of a journey event 200 or an exit event 230 or anintersection event 240. Here, the path is a linear segment asillustrated in FIG. 11d but alternatively the path segment could becurvilinear or a combination of linear and curvilinear.

Before entering the speed event 250, the mobile device 11 is in asegment of mobile device-remote observation alignment at point G with acorresponding log of mobile device vector data 82 and transmission to aremote device 44.

During the speed event 250, the mobile telemetry hardware system 30senses a segment of mobile device-remote observation misalignment risk220. A series of mobile device vector data (222, 224) are logged and canbe transmitted from the mobile device telemetry hardware system 30 to aremote device 44 more frequently in time. In an embodiment of theinvention, the log contains a larger sample of mobile device vector datapoints communicated less frequently in time. Then the mobile device 11enters into a segment of mobile device-remote observation alignment atpoint H and another log of mobile device vector data 83 is created andtransmitted from the mobile telemetry hardware system 30 to a remotedevice 44. Upon receipt of the log of mobile device vector data, theremote device 44 renders the data adaptively to provide a graphicalimage 54 on a map 50 of the remote device 44.

Sensing mobile device-remote observation misalignment risk can occur ina number of different ways. In an embodiment of the invention, sensingoccurs when a heading changes beyond a defined limit triggering thereconcile of mobile device-remote observation alignment. In anotherembodiment of the invention, sensing occurs when a speed changes beyonda defined limit triggering the reconcile of mobile device-remoteobservation alignment. In another embodiment of the invention, sensingoccurs when a number of raw data points have been sampled triggering areconcile of mobile device-remote observation alignment.

Mobile Device Furtherance Visualization System Process Calibration andRecalibration

Calibration and recalibration of the mobile device furtherancevisualization system process is next described with reference to FIGS.12a and 12 b.

Calibration begins by selecting the furtherance visualization systemstate transition conditions. The conditions may be based on one or moreof the position, speed, heading or portion of a longer path segment(complete journey) represented by a number of raw data points of mobiledevice vector data. Then, based upon the selected state transitionconditions, the reconcile mobile device-remote observation alignmentparameters are set for the furtherance visualization system mobiledevice distributed process. Adaptive render parameters are also basedupon the selected transition conditions and correlated to the reconcilemobile device-remote observation alignment parameters are set for thefurtherance visualization system remote device distributed process. Thecorrelation provides an appropriate relative mobile device-remoteobservation timing and phase shift between the furtherance visualizationsystem mobile device distributed process and the the remote devicedistributed process.

The furtherance visualization system process may also be recalibrated tofurther refine or adjust the appropriate relative timing and phaseshift. Recalibration begins with a check of the phase shift between thereconcile mobile device-remote observation alignment parameters and theadaptive render parameters. The check determines if the amount ofpredictive render is acceptable between the receipts of subsequent logsof mobile device vector data. Predictive render is acceptable when thepredictive render does not introduce any rendering errors on the map 50of a graphical display. If the appropriate timing and phase shift is notacceptable, then recalibrate the reconcile mobile device-remoteobservation alignment parameters for the furtherance visualizationsystem mobile device distributed process or recalibrate the adaptiverender parameters for the mobile device furtherance visualization systemremote device distributed process.

For example, in an embodiment of the invention the number of data pointsin a log of mobile device vector data are reduced by a pathsimplification process. A log of mobile device vector data iscommunicated periodically to the remote device. Persons skilled in theart will appreciate there are a number of approaches to reduce the datapoints representative of a path segment such as the Ramer DouglasPeucker approach, Douglas Peucker approach, iterative end point fitapproaches, polyline reductions and split and merge approaches. For thisembodiment, the furtherance visualization system state transitionconditions are based upon a portion of a path segment and number of rawdata points and associated time stamps. The reconcile mobiledevice-remote observation alignment parameters are then set to a sampleof 100 raw data points to define the portion of a path segment travelledby the mobile device 11 over time for this example embodiment. Samplingof the 100 raw data points is one sample per second. The adaptive renderparameters and then set to a range between −4.5 seconds and −13.5seconds. The adaptive render parameters provide for a phase shiftbetween the distributed processes. Recalibration of the furtherancevisualization system process of this embodiment may result in adifferent set or refinement of the parameters. For example, the adaptiverender parameters may be set more precisely to 9.0 seconds to providebetter calibration. Alternatively, the sample of 100 raw data points todefine the portion of the path segment could be reduced to a smallersample less than 100 for the reconcile mobile device-remote observationalignment parameters or a larger sample greater than 100 as long as theparameters are calibrated and correlated within the system process.

In another embodiment of the invention, the communication and frequencyof logs of mobile device vector data are reduced and based upon eventssuch as the speed and the heading of the mobile device 11. For arelatively constant speed and heading, the logs are not communicated tothe remote device 44. When speed or heading changes beyond a limit, thenthe log of mobile device vector data is communicated aperiodically tothe remote device. The reconcile mobile device-remote observationalignment parameters are set to a speed or heading limit. These limitsinitiate a reconcile of mobile device-remote observation alignment andcommunication of a subsequent log of mobile device vector data to aremote device. The adaptive render parameters are then set to a range oftime to provide the phase shift between the distributed processes.Recalibration of the furtherance visualization system process for thisembodiment may result in a different set of parameters. For example, theadaptive render parameters may be set to more narrow range or precisenumber in seconds for the phase shift. Alternatively, the speed changelimit may be adjusted, or the heading change limit may be adjusted. Therecalibration may also be a combination of adjusted or differentparameters for both the reconcile mobile device-remote observationalignment or adaptive render parameters.

Mobile Device Furtherance Visualization System Mobile Distributed Logic

The first distributed process and furtherance visualization logic anddetermination of alignment or misalignment risk are next described withreference to FIGS. 13a and 13b . The mobile device logic is generallyillustrated at 280 and the check reconcile mobile device-remoteobservation alignment parameter logic is generally indicated at 290.

The mobile device furtherance visualization system distributed processis initially calibrated with furtherance visualization reconcile mobiledevice-remote observation alignment parameters. The furtherancevisualization reconcile mobile device-remote observation alignmentparameters may also be recalibrated during operation of the process. Aninitial log of mobile device vector data is communicated from the mobiletelemetry hardware system 30 to a remote device 44. Then, the mobiledevice 11 is monitored and another subsequent log of mobile devicevector data is generated and stored in memory of the mobile telemetryhardware system 30. The microprocessor 31 and firmware executing themobile device furtherance visualization logic is capable to check thereconcile mobile device-remote observation alignment parameters. If thealignment is in mobile device-remote observation alignment, continue tomonitor the mobile device and log mobile device vector data. If thealignment is in mobile device-remote observation misalignment risk, thenenable a reconciliation for a mobile device-remote observationmisalignment risk and communicate the subsequent log of mobile devicevector data to a remote system 44. The logic continues and returns tomonitor the mobile device 11 and log mobile device vector data.

The check for reconcile mobile device-remote observation alignmentbegins with a determination of the mobile device position. If theposition is varying beyond limits, then set mobile device-remoteobservation misalignment risk. If the position is relatively constant orvarying within limits, check the mobile device speed. If the speed isincreasing or decreasing beyond limits, set mobile device-remoteobservation misalignment risk. If the speed is relatively constant orvarying within limits, check the mobile device heading. If the headingis increasing or decreasing beyond limits, set mobile device-remoteobservation misalignment risk. If the heading is relatively constant orvarying within limits, set mobile device-remote observation alignment.If the path segment has reached (equal or greater than) the maximumnumber of raw data points (example of 100 raw data points), then setmobile device-remote observation misalignment risk. If the path segmenthas not reached (less than) the maximum number of raw data points(example 100 raw data points), then set mobile device-remote observationalignment.

In an embodiment of the invention, the mobile device parameters ofposition, speed and heading may be checked in any logical order ofposition, speed, heading or path segment. In another embodiment of theinvention, the check may be one or more of the reconcile mobiledevice-remote observation alignment parameters (position, or speed, orheading, or path segment) to determine a mobile device-remoteobservation misalignment risk. Optionally, the mobile device may alsocommunicate a heartbeat message to a remote device. The heartbeatmessage signals normal operation and alignment of the mobile device tothe remote device during longer periods of time between subsequent logsof mobile device vector data.

The mobile telemetry hardware system 30 including the DTE telemetrymicroprocessor 31, non-volatile flash memory 35 and firmware execute thelogic of the first distributed process. In embodiments of the invention,the GPS module 33, either integral with the mobile telemetry hardwaresystem 30 or external to the mobile telemetry hardware system 30 providemobile device vector data. Alternatively, mobile device vector data maybe provided over the vehicle network communications bus 37 to theinterface 36 to the DTE telemetry microprocessor 31 and non-volatileflash memory 35. The DCE wireless telemetry communicationsmicroprocessor 32 integral with the mobile telemetry hardware system 30or alternatively an external DCE wireless telemetry communicationsmicroprocessor 32 provides the capability to communicate mobile devicevector data.

Remote Device Furtherance Visualization System Distributed Logic

The second distributed process and furtherance visualization systemlogic is next described with reference to FIG. 14. The remote devicefurtherance visualization system distributed process is initiallycalibrated with adaptive render parameters for a phase shift. Theadaptive render parameters may also be recalibrated during operation ofthe process.

The initial log of mobile device vector data is received from the mobiletelemetry hardware system 30. A mobile device 11 is adaptive rendered ona graphical display based upon the sequence of data points andassociated time stamps contained in the initial log of mobile devicevector data. Then, the remote device 44 receives a subsequent log ofmobile device vector data. The mobile device 11 is adaptive rendered ona graphical display based upon the sequence of data points contained inthe subsequent log of mobile device vector data and the phase shift. Theprocess repeats for each receipt of subsequent logs of mobile devicevector data.

In an embodiment of the invention, the adaptive render is a phase shift.In another embodiment of the invention, the adaptive render includes adata render. In another embodiment of the invention, the adaptive renderincludes a predictive render. The phase shift is calibrated to reducethe amount of predictive render or to limit the amount of mobiledevice-remote observation misalignment risk.

A microprocessor and memory on the server 19, or the computing device 20execute the logic of the second distributed process. The seconddistributed process may also be incorporated into a fleet managementsoftware program 10 that executes on a server 19 or a computing device20.

Embodiments of the present invention provide one or more technicaleffects. More specifically, an ability to maintain a mobiledevice-remote observation alignment between a mobile device and a remotedevice for receiving logs of mobile device vector data and rendering agraphical image of the mobile device on a graphics display. Anotherability to sense a mobile device-remote observation misalignment riskbetween the mobile device and the remote device and communication of alog of mobile device vector data to reconcile mobile device-remoteobservation alignment. An adaptive render with a calibrated phase shiftincluding the ability to render based upon data from the log of mobiledevice vector data and the ability to render predictively when requireduntil receipt of a subsequent log of mobile device vector data. Anotherability to calibrate the adaptive render with the reconcile mobiledevice-remote observation alignment to minimize the predictive renderwhen required.

The description of present invention is with respect to the disclosednon-limiting embodiments and persons skilled in the art understand thatthe invention is not limited to the disclosed non-limiting embodiments.Persons skilled in the art further understand that the disclosedinvention intends to cover various modifications and equivalentarrangements included within the scope of the appended claims. Thus, thepresent invention is not limited by any of the described non-limitingembodiments.

What is claimed is:
 1. A telematics furtherance visualization methodcomprising: a first distributed process for a mobile device, a seconddistributed process for a remote device, said first distributed processcommunicating data to said second distributed process, said firstdistributed process monitoring said mobile device, said firstdistributed process logging mobile device vector data of said mobiledevice and communicating the mobile device vector data of said mobiledevice to said remote device, and said first distributed process sensinga mobile device-remote observation misalignment risk when the mobiledevice enters a segment of travel of increased risk that the remoteobservation of the mobile device at the remote device will be misalignedfrom the path of travel of the mobile device.
 2. A telematicsfurtherance visualization method as in claim 1, wherein said firstdistributed process reconciling mobile device-remote observationalignment to align the path of travel of the mobile device with theremote observation of the mobile device at the remote device.
 3. Atelematics furtherance visualization method as in claim 2, wherein saidsecond distributed process adaptive rendering on a map of said remotedevice a graphical image of said mobile device based on said mobiledevice vector data.
 4. A telematics furtherance visualization method asin claim 3, whereby the graphical image on the map of said remote deviceis aligned with the path of travel of said mobile device, therebyproviding mobile device-remote observation alignment.
 5. A telematicsfurtherance visualization method as in claim 1, wherein said mobiledevice-remote observation misalignment risk includes mobiledevice-remote observation alignment parameters, and wherein said seconddistributed process adaptive rendering on a map of said remote device agraphical image of said mobile device based on said mobile device vectordata, wherein said adaptive rendering includes adaptive renderparameters, and said method further comprises correlating said mobiledevice-remote observation alignment parameters and said adaptive renderparameters.
 6. A telematics furtherance visualization method as in claim5, wherein said reconciling mobile device-remote observation alignmentto align the path of travel of the mobile device with the remoteobservation of the mobile device at the remote device includescommunicating a subsequent log of said mobile device vector data of saidmobile device to said remote device.
 7. A telematics furtherancevisualization method as in claim 6, wherein said mobile device vectordata comprises at least one data point of a position indication, a speedindication or a heading indication of said mobile device and at leastone time stamp associated with each said data point.
 8. A telematicsfurtherance visualization method as in claim 6, wherein said mobiledevice-remote observation alignment parameters are based upon at leastone of a position limit, a speed limit, a heading limit or a pathsegment limit.
 9. A telematics furtherance visualization method as inclaim 6, wherein said adaptive render parameters are based upon at leastone of a phase shift, a data render, or a predictive render.
 10. Atelematics furtherance visualization method as in claim 6, wherein saidmobile device-remote observation alignment parameters are based upon atleast one of a position limit, a speed limit, a heading limit or a pathsegment limit, and wherein said adaptive render parameters are basedupon at least one of a phase shift, a data render, or a predictiverender.
 11. A telematics furtherance visualization method as in claim 6,wherein said mobile device-remote observation alignment parameters arebased upon a combination of at least two of a position limit, a speedlimit, a heading limit, or a path segment limit.
 12. A telematicsfurtherance visualization method as in claim 6, wherein said adaptiverender parameters are based upon a combination of at least two of aphase shift, a data render, or a predictive render.
 13. A telematicsfurtherance visualization method as in claim 6, further comprisingcorrelating said mobile device-remote observation alignment parametersand said adaptive render parameters to command a predictive render. 14.A telematics furtherance visualization method as in claim 6, furthercomprising calibrating said mobile device-remote observation alignmentparameters and said adaptive render parameters to command a predictiverender.
 15. A telematics furtherance visualization method as in claim 6,wherein sensing a potential mobile device-remote observationmisalignment risk is based upon checking said mobile device remoteobservation alignment parameters.
 16. A telematics furtherancevisualization method as in claim 15, wherein said checking said mobiledevice-remote observation alignment parameters enables reconcilingmobile device-remote observation alignment.
 17. A telematics furtherancevisualization method as in claim 6, wherein said adaptive rendering isbased upon said adaptive render parameters.
 18. A telematics furtherancevisualization method as in claim 6, further comprising recalibratingsaid mobile device-remote observation alignment parameters and saidadaptive render parameters.
 19. A telematics furtherance visualizationmethod as in claim 6, further comprising recalibrating at least one ofsaid mobile device-remote observation alignment parameters or saidadaptive render parameters.
 20. A telematics furtherance visualizationmethod as in claims 6, further comprising communicating a heartbeatmessage to said remote device to further command a predictive render.21. A telematics mobile device visualization apparatus comprising: atleast one mobile device, said at least one mobile device including amicroprocessor, memory and firmware, said microprocessor, memory andfirmware capable of executing a first distributed process, at least oneremote device, said at least one remote device including amicroprocessor, memory and software, said microprocessor, memory andsoftware capable of executing a second distributed process, said atleast one mobile device and said at least one remote device capable ofcommunication, a first distributed process for a mobile device, a seconddistributed process for a remote device, said first distributed processcapable of communicating data to said second distributed process, saidfirst distributed process capable to monitor said mobile device to logmobile device vector data of said mobile device and communicate themobile device vector data of said mobile device to said remote device,said first distributed process capable to sense a mobile device-remoteobservation misalignment risk when the mobile device enters a segment oftravel of increased risk that the remote observation of the mobiledevice at the remote device will be misaligned from the path of travelof the mobile device.
 22. A telematics furtherance visualizationapparatus as in claim 21, wherein said first distributed process capableto reconcile mobile device-remote observation alignment to align thepath of travel of the mobile device with the remote observation of themobile device at the remote device.
 23. A telematics furtherancevisualization apparatus as in claim 22, wherein said second distributedprocess capable to adaptive render on a map of said remote device agraphical image of said mobile device based on said mobile device vectordata.
 24. A telematics furtherance visualization apparatus as in claim23, whereby the graphical image on the map of said remote device isaligned with the path of travel of said mobile device, thereby providingmobile device-remote observation alignment.
 25. A telematics furtherancevisualization apparatus as in claim 21, wherein said mobiledevice-remote observation misalignment risk includes mobiledevice-remote observation alignment parameters, and wherein said seconddistributed process capable to adaptive render on a map of said remotedevice a graphical image of said mobile device based on said mobiledevice vector data, wherein said adaptive render includes adaptiverender parameters, and said mobile device-remote observation alignmentparameters and said adaptive render parameters are correlated.
 26. Atelematics furtherance visualization apparatus as in claim 25, whereinsaid reconcile mobile device remote observation alignment to align thepath of travel of the mobile device with the remote observation of themobile device at the remote device includes communicate a subsequent logof said mobile device vector data of said mobile device to said remotedevice.
 27. A telematics furtherance visualization apparatus as in claim26, wherein said mobile device vector data comprises at least one datapoint of a position indication, a speed indication or a headingindication of said mobile device and at least one time stamp associatedwith each said data point.
 28. A telematics furtherance visualizationapparatus as in claim 26, wherein said mobile device-remote observationalignment parameters are based upon at least one of a position limit, aspeed limit, a heading limit or a path segment limit.
 29. A telematicsfurtherance visualization apparatus as in claim 26, wherein saidadaptive render parameters are based upon at least one of a phase shift,a data render, or a predictive render.
 30. A telematics furtherancevisualization apparatus as in claim 26, wherein said mobiledevice-remote observation alignment parameters are based upon acombination of at least two of a position limit, a speed limit, aheading limit, or a path segment limit.
 31. A telematics furtherancevisualization apparatus as in claim 26, wherein said adaptive renderparameters are based upon a combination of at least two of a phaseshift, a data render, or a predictive render.
 32. A telematicsfurtherance visualization apparatus as in claim 26, wherein said mobiledevice-remote observation alignment parameters and said adaptive renderparameters are correlated to command a predictive render.
 33. Atelematics furtherance visualization apparatus as in claim 26, whereinsaid mobile device-remote observation alignment parameters and saidadaptive render parameters are calibrated to command a predictiverender.
 34. A telematics furtherance visualization apparatus as in claim26, wherein said capable to sense a potential mobile device-remoteobservation misalignment risk is based upon checking said mobile deviceremote observation alignment parameters.
 35. A telematics furtherancevisualization apparatus as in claim 34, wherein said checking saidmobile device-remote observation alignment parameters enables saidreconcile mobile device remote observation alignment.
 36. A telematicsfurtherance visualization apparatus as in claim 26, wherein said capableto adaptive render is based upon said adaptive render parameters.
 37. Atelematics furtherance visualization apparatus as in claim 26, whereinsaid mobile device-remote observation alignment parameters and saidadaptive render parameters are recalibrated.
 38. A telematicsfurtherance visualization apparatus as in claim 26, wherein at least oneof said mobile device remote observation alignment parameters or saidadaptive render parameters is recalibrated.
 39. A telematics furtherancevisualization apparatus as in claim 26, further including a heartbeatmessage communicated to said remote device to further command apredictive render.